> ## Documentation Index
> Fetch the complete documentation index at: https://docs.magickml.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Float

# Math Subtract Float

The Math Subtract Float node performs subtraction on two floating-point numbers. It takes two input values, subtracts the second value from the first, and outputs the result.

## Inputs

1. `a` (float, default: 0): The first value in the subtraction operation.
2. `b` (float, default: 0): The second value in the subtraction operation, which will be subtracted from `a`.

## Outputs

1. `result` (float): The result of subtracting `b` from `a`.

## Configuration

This node has no additional configuration options.

## Usage

To use the Math Subtract Float node:

1. Add the Math Subtract Float node to your spell.
2. Connect the `a` input to the first value you want to subtract from.
3. Connect the `b` input to the value you want to subtract.
4. The `result` output will contain the result of the subtraction operation.

## Example

Here's an example of how to use the Math Subtract Float node in a spell:

```
1. Add a Trigger node and set it to "On App Start".
2. Add a Math Subtract Float node.
3. Add two Number nodes and set their values to 10.5 and 3.7.
4. Connect the first Number node to the `a` input of the Math Subtract Float node.
5. Connect the second Number node to the `b` input of the Math Subtract Float node.
6. Add a Debug Log node and connect the `result` output of the Math Subtract Float node to its `message` input.
7. Run the spell.
```

The Debug Log will output the result of 10.5 - 3.7, which is 6.8.

## Best Practices

* Ensure that the input values are valid floating-point numbers. Non-numeric inputs may cause unexpected behavior.
* Remember that the order of inputs matters: `a` is the value being subtracted from, and `b` is the value being subtracted.

## Common Issues

* If either input is not a valid floating-point number, the node may output `NaN` (Not a Number) or an unexpected result.
* Be cautious when subtracting very large or very small numbers, as floating-point precision limitations may affect the accuracy of the result.